Wavelet Analysis of Fluctuations in the Thickness of Cold-Rolled Strip

Abstract

Results are presented from a wavelet analysis of fluctuations in the thickness of strip that was cold-rolled during vibration of the mill's roll system. The vibrations were caused by a problem with the reduction gear in the main line of the mill. Results obtained by using the software Deform 2D to model the process of In connection with the continual elevation of standards on the quality of rolled products and the concept of "defect-free manufacturing" (1), more importance is being attached to studies directed toward identifying and eliminating the causes of longi- tudinal and transverse thickness variations in rolled strip and fluctuations in the quality of its surface (2-4). When analyzing fluc- tuations in the dimensions of strip, attention should also be paid to the factors that result in periodic changes in thickness along the length of the rolled product - factors such as vibration. To minimize deviations in the operation of rolling mills that affect the accuracy of the rolled product, it is expedient to study the formation of the products' geometric dimensions as part of the process of designing the rolling mill. This will make it possible to determine the ranges of variation of the parameters of the mill's mech- anisms that are tolerable from the standpoint of their effect on the accuracy of the rolled product. Among these parameters are the maximum allowable vibrations of elements of the mill's stand. It is best to use computer modeling to perform such studies and to use a highly sensitive method such as wavelet analysis to analyze the formation of the product's geometric dimensions. The goal of our investigation was to take the results obtained from wavelet analysis of the thickness of strip that was cold-rolled on a mill with a system of rolls which was vibrating due to malfunctioning of the reduction gear in its main line and compare those results to results obtained by using the software environment Deform 2D to model the operation of rolling with vibrations. Wavelet analysis began to be used relatively recently in scientific research (5-7). Wavelets (8) - which in some pub- lications have been called "spikes" (9) - are used to analyze information, rid signals of noise, compress data, identify short- term and global patterns, and subject signal components to spectral analysis. Wavelet transformation makes it possible to eval- uate not only the frequency spectrum of a signal but also determine the moment that a given harmonic appeared. Wavelet analysis is very informative because it gives researchers an added degree of freedom in the analysis by allowing them to